1. Field of the Invention
The present invention relates to an individual authentication technique that uses a face data in the field of biometric authentication. In particular, the present invention relates to 3-dimensional face data registering, restoring and collating system and method, in which it is aimed to improve reduction of authentication accuracy caused due to change in a facing orientation, lighting, which are obstructions to perform face authentication.
2. Description of the Related Art
A process of an individual authentication system using the biometrics is separated into a “registering process” for registering a data of an authentication target to a database in advance, and a “collating process” for determining a likelihood that indicates whether or not an image is likely to be of the target by collating a target image with images data registered in the database one by one.
The face authentication uses a feature data of a face as the data to be registered and collated. The mainstream of a method for extracting the face feature data is a method that uses a 2-dimensional front face image, which is disclosed in “Recognition of Faces by Computers—Survey” by Shigeru Akamatsu, (IEICE (The Institute of Electronics, Information and Communication Engineers) Journal A Vol. J, 80-A, No. 8, August, 1997, pp. 1215-1230: first conventional example). As a specific methods, there are methods that are disclosed in the first conventional example, e.g. a “structural base method” in which the face parts such as eyes, a nose, and a mouth are detected from a 2-dimensional face image, and the face features are recognized and collated based on geometric characteristics of those parts, and a “pattern matching method” in which contrast values of the 2-dimensional face image are regarded as a set of vectors, and a peculiar face is calculates through an analysis of the main component thereof to recognize and collate the feature of the face. Both of these methods extract feature quantities form the 2-dimensional face image, and calculate the likelihood through a comparison and collation.
However, these methods for extracting the feature quantities from the 2-dimensional face image are likely to be affected by factors such as a facing orientation, lighting, and expression, which are different from those at the time of registration, and by secular changes due to over the years from the time of the registration. To deal with this, there are known face authentication systems which use the 3-dimensional data face to reduce the affect of those change factors, as disclosed in Japanese Laid Open Patent Applications (JP-P2004-086929A and JP-A-Heisei 09-259271: second and third conventional examples). In addition, a method is studied that restores a 3-dimensional face shape data from 2-dimensional face images of a front face image, a profile, and the like, without using a 3-dimensional face measuring apparatus as disclosed in “A Morphable Model for The Synthesis of 3D Faces” by Volker Blanz, and Thomas Vetter (SIGGRAPH99, 1999: fourth conventional example).
In conjunction with the above description, an image processing apparatus is disclosed in Japanese Laid Open Patent Application (JP-P2001-229400A). The image processing apparatus in this conventional example has an image input section for inputting a face image. A display section displays the face image inputted from the image input section and a message for prompting a user to specify a display position of a facial part of the face image. An input section used to input an optional point on the display. A facial part extracting section sets the point inputted from the input section as an origin and extracts another facial part based on the origin. An image generating section generates a 3-dimensional image based on the facial parts extracted by the facial part extraction section and coordinate data of the inputted origin.
Also, an image collating apparatus is disclosed in Japanese Laid Open Patent Application (JP-P2004-185386A). The image collating apparatus in this conventional example collates a first 2-dimensional image and a second 2-dimensional image. An image converting section converts the first 2-dimensional image into a 3-dimensional image. A direction detecting section detects a picking direction of a target in the second 2-dimensional image. An image generating section generates a third 2-dimensional image when the target is seen from the direction based on the 3-dimensional image. An image collating section collates the second 2-dimensional image and the third 2-dimensional image.
Also, a face recognizing apparatus is disclosed in Japanese Laid Open Patent Application (JP-A-Heisei 4-242106). In the face recognizing apparatus in this conventional example, a shape measuring section measures 3-dimensional shape of a face in X-, Y-, and Z-directions. A correcting section corrects a face orientation based on a 3-dimensional shape data. A feature point extracting section extracts feature points of the face based on the corrected 3-dimensional shape data. A collating section collates the extracted feature points and feature points on a database. The correcting section includes a first correcting section directions around the Y-axis and the Z-axis, and a second correcting section a direction around the X-axis. The second correcting section rotates the feature data around the X-axis in correspondence with a line on the Y-Z plane corresponding to an angle θ between the Y-axis and a line corresponding to a ridgeline of a nose obtained as the feature points on the Y-Z plane.
In the face authentication system of the above-described conventional examples, it is necessary to supply the 3-dimensional face data in the registering process or the collating process. For this purpose, an expensive 3-dimensional face measuring apparatus is required. Also, it requires a picking-up time of several hundreds milliseconds for the measurement, which is longer than that of a still camera. Thus, there are various kinds of problems which are the obstacles for putting it into a practical use.
Further, identification/selection of suspects in criminal investigations can be considered as an object for introducing the face authentication system. However, it is necessary to build up a database of criminals by using the 3-dimensional face measuring device. Thus, a great amount of resources are required to perform 3-dimensional face measurement additionally, etc. For this reason, the system cannot be effectively operated for a long period from the time point that the system is introduced until data are sufficiently registered on the database.
Moreover, in the method disclosed in the fourth conventional example, in which the 3-dimensional data of the face is restored from the 2-dimensional images of a front face image or a profile image without using the 3-dimensional face measuring apparatus, it can be considered that the 3-dimensional face measuring apparatus becomes unnecessary by restoring the 3-dimension face shapes from face photographs of criminals that are stored through criminal investigations and registering these data to the database. However, in this method, restoration of the face is performed by referring to the 3-dimensional face measured shape of others. Therefore, sufficient restoration accuracy cannot be obtained if there are only a small number of 3-dimensional face measured shapes. Thus, it is a critical problem for this method to increase the number of the 3-dimensional face measured shapes for reference.
As described, the first problem in the above-described conventional examples is that the face authentication system using the 3-dimensional data in the criminal investigations or the like cannot be operated effectively for a long period from the time point that the system is introduced. The reason is that it does not function as the system unless there is a sufficient amount of measured data obtained by using the 3-dimensional face measuring apparatus stored in the registered database. In particular, a considerable number of registered data is required for the system to be used effectively in the criminal investigations, so that a loss-time is generated for an extremely long term.
Further, the second problem is that the restoration accuracy is reduced when the database is built by using the technique for restoring the 3-dimensional shape of the face from the 2-dimensional face images of a front face image and a profile image without using the 3-dimensional face measuring apparatus. The reason is that the restoration accuracy in the technique for restoring the 3-dimensional face shape depends on the number of 3-dimensional face measured shapes of others for reference. Sufficient restoration accuracy cannot be obtained when the number is small.